Abstract
This paper presents an approach for dealing with imprecision in performance evaluation analysis focused particularly on Public Policy but applicable to other fields. While most previous research builds fuzzy indicators by assessing a membership function as the indicator itself, with direct subjective evaluation, this new approach is based on the fuzzification of crisp indicators which are subject to imprecision, vagueness or an incomplete perception of reality. These indicators may be quantitative or qualitative yet approximate expressions from real data in order to define results and systematize the information. The evaluation process is based on those expressions and uses fuzzy distances as a performance evaluation tool to show the degree of efficacy related to both crisp and fuzzy targets set as the reference value in the evaluation process.
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